Self Driving Car
Self-driving car research aims to create vehicles capable of navigating and operating without human intervention, prioritizing safety and efficiency. Current efforts concentrate on improving perception (using cameras, LiDAR, and sensor fusion), planning robust and comfortable trajectories (employing reinforcement learning, optimization-based methods, and hybrid approaches), and handling complex scenarios like multi-agent interactions and adverse weather conditions. These advancements are crucial for enhancing road safety, optimizing traffic flow, and revolutionizing transportation systems.
Papers
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AutoExp: A multidisciplinary, multi-sensor framework to evaluate human activities in self-driving cars
Carlos Crispim-Junior, Romain Guesdon, Christophe Jallais, Florent Laroche, Stephanie Souche-Le Corvec, Laure Tougne Rodet
Introduction to Latent Variable Energy-Based Models: A Path Towards Autonomous Machine Intelligence
Anna Dawid, Yann LeCun